GPT-5 Mini vs GPT-OSS 120B
Compare GPT-5 Mini and GPT-OSS 120B. Find out which one is better for your use case.
Model Comparison
| Feature | GPT-5 Mini | GPT-OSS 120B |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Model Type | text | text |
| Context Window | 400,000 tokens | 131,072 tokens |
| Input Cost | $0.25 / 1M tokens | $0.00 / 1M tokens |
| Output Cost | $2.00 / 1M tokens | $0.00 / 1M tokens |
Strengths & Best Use Cases
GPT-5 Mini
1. High reasoning performance
- Retains strong reasoning capabilities despite being a smaller, faster model.
- Suitable for tasks requiring accurate logic and structured thinking.
2. Fast and cost-efficient
- Optimized for speed, making it ideal for real-time or high-volume workloads.
- Far cheaper than GPT-5 while maintaining solid capability.
3. Great for well-defined tasks
- Excels when prompts are precise and objectives are clearly specified.
- More predictable and stable for deterministic workflows.
4. Multimodal input
- Accepts text + image as input.
- Outputs text only.
5. Tool support
- Works with Web Search, File Search, Code Interpreter, MCP.
- (Does not support Image Generation as a tool and does not support Computer Use.)
GPT-OSS 120B
1. Most powerful open-weight model
- 117B parameters (5.1B active) while fitting on a single H100 GPU.
- High reasoning quality compared to other open models.
2. Apache 2.0 license
- Fully permissive, no copyleft or patent restrictions.
- Safe for commercial products, research, and redistribution.
3. Configurable reasoning effort
- Supports adjustable reasoning: low, medium, high.
- Lets developers balance latency vs. depth.
4. Full chain-of-thought access
- Unlike closed commercial models, this exposes complete reasoning traces.
- Useful for debugging, auditing, safety research, and transparency.
5. Fine-tunable
- Fully supports parameter fine-tuning.
- Can be adapted to domain-specific workflows and proprietary datasets.
6. Agentic capabilities
- Built-in function calling.
- Native support for web browsing, Python execution, and structured outputs.
- Ideal for open-source agents, full-stack automation, and developer tooling.
7. Tooling ecosystem support
- Compatible with Chat Completions, Responses API, Assistants, Realtime, Batch, and Fine-tuning endpoints.
- Supports Image Generation, Code Interpreter (via Python runtime), and more.
8. Open-source availability
- Downloadable on HuggingFace for local or on-prem deployment.
- Supports full offline, private, or self-hosted usage.
9. Streaming + function calling support
- Real-time interactions.
- Strong for interactive agents, coding assistants, and UI-driven workflows.
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